Abstract

In the past 20 years great progress has been made in the development of multidimensional
outcome measures (such as the Disease Activity Score and ACR20) to evaluate treatments
in rheumatoid arthritis, a process disseminated throughout rheumatic diseases. These
outcome measures have standardized the assessment of outcomes in trials, making it
possible to evaluate and compare the efficacy of treatments. The methodologic advances
have included the selection of pre-existing outcome measures that detected change
in a sensitive fashion (in rheumatoid arthritis, this was the Core Set Measures).
These measures were then combined into a single multidimensional outcome measure and
such outcome measures have been widely adopted in trials and endorsed by the American
College of Rheumatology (ACR) and the European League Against Rheumatism (EULAR) and
regulatory agencies. The secular improvement in treatment for patients with rheumatoid
arthritis has been facilitated in part by these major methodologic advancements. The
one element of this effort that has not optimized measurement of outcomes nor made
it easier to detect the effect of treatments is the dichotomization of continuous
measures of response, creating responders and non-responder definitions (for example,
ACR20 responders; EULAR good responders). Dichotomizing response sacrifices statistical
power and eliminates variability in response. Future methodologic work will need to
focus on improving multidimensional outcome measurement without arbitrarily characterizing
some patients as responders while labeling others as non-responders.